PeopleofSuperintelligence

Researcher

Bernhard Pfahringer

Bernhard Pfahringer is a machine-learning researcher whose work includes multi-label classification and learning from changing data streams. He completed undergraduate study in 1985 and a PhD in 1995 at the Vienna University of Technology, then joined Waikato's Machine Learning Group as a postdoctoral fellow in 1996. At Waikato, he became a Senior Lecturer in 2000 and an Associate Professor in 2007, then coauthored a multi-label classification paper in 2008 and the MOA online-learning environment in 2010. Waikato scheduled his inaugural lecture, “Dawn of the Age of Data,” for October 2015; his later papers introduced incremental decision trees in 2019 and stream hyperparameter tuning in 2025. As of October 2026, he is a Professor at Waikato and Co-Director of the Artificial Intelligence Institute.

Works
389
Citations
32,805
h-index
53
Badges

Publication numbers from OpenAlex, as of 22 October 2026.

Timeline

  1. 1985–1995

    Degrees at Vienna University

    He completes undergraduate study in 1985 and a PhD in 1995, both at the Vienna University of Technology.

  2. 1996–2007

    Appointments at Waikato

    He joins Waikato's Machine Learning Group as a postdoctoral research fellow in 1996 for one year. He begins work as a Senior Lecturer in the Computer Science Department in 2000 and becomes an Associate Professor in 2007.

  3. 2008

    Pruned sets for classification

    In 2008, he coauthors Multi-label classification using ensembles of pruned sets with Jesse Read and Geoffrey Holmes. The method treats sets of labels as single labels to capture correlations between labels.

  4. 2010

    MOA for online learning

    In 2010, he coauthors MOA: Massive Online Analysis, a software environment that implements online and offline methods and provides tools for evaluation in online learning from evolving data streams.

  5. October 2015

    Dawn of the Age of Data

    In October 2015, Waikato schedules him to deliver his Inaugural Professorial Lecture, “Dawn of the Age of Data,” on how data from smart meters and fitness trackers can reveal patterns that help predict trends and preferences.

  6. 2019

    Stochastic Gradient Trees

    In 2019, he coauthors Stochastic Gradient Trees, a method for learning decision trees incrementally with stochastic gradient information.

  7. 2025

    Bayesian Stream Tuner

    In 2025, he coauthors Bayesian Stream Tuner, a framework for online hyperparameter optimization in non-stationary data streams.

  8. As of October 2026

    AI Institute co-director

    As of October 2026, he is a Professor at the University of Waikato and Co-Director of its Artificial Intelligence Institute.

Career

  1. Since 1996University of WaikatoPostdoctoral research fellow, Senior Lecturer
  2. 2017–2021University of Auckland
  3. 1986–1994University of Vienna
  4. 1985–1996Austrian Society for Cybernetic Studies

Education

  1. 1995TU WienPhD
  2. 1985TU WienUndergraduate study

From the biography and OpenAlex affiliations (the years of papers that list the organization), so some years are approximate.

  1. The United States employs an estimated 48% of people shaping AIIncludes University of Waikato. We estimate where the people shaping AI work today, how universities, companies and research institutes split across countries, and how country shares have changed since the 1960s.
  2. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes University of Waikato. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.
  3. Google has the highest combined h-index among AI organizationsIncludes University of Waikato. We estimate that Google holds the highest combined h-index at 8,016, while universities account for 73% of the deduplicated total across AI organizations.
  4. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes University of Vienna. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other university. We compare doctorate and 5+ year employment links, career timing and current workplaces for 187 major-prize and 1,111 best-paper winners.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

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  1. Inaugural Professorial Lecture Series 2015 | University of Waikato waikato.ac.nz. Checked 21 October 2026.
  2. Multi-label classification using ensembles of pruned sets researchcommons.waikato.ac.nz. Checked 21 October 2026.
  3. MOA: Massive Online Analysis jmlr.org. Checked 21 October 2026.
  4. Stochastic Gradient Trees proceedings.mlr.press. Checked 21 October 2026.
  5. Bayesian Stream Tuner: Dynamic Hyperparameter Optimization for Real-Time Data Streams researchportal.ip-paris.fr. Checked 21 October 2026.
  6. About, TuiML Documentation tuiml.ai. Checked 21 October 2026.